The Impact of Climate Change on Ski Resort Operations and
Development: Opportunities and Threats
By
Daniel D. D. McGill
B.S., Human and Organizational Development, 1999
Vanderbilt University
Submitted to the Department of Urban Studies and Planning in partial fulfillment of the
requirements for the degree of
Master of Science in Real Estate Development
at the
Massachusetts Institute of Technology
September 2007
© Daniel D. D. McGill All Rights Reserved.
The authors hereby grant MIT permission to reproduce and publicly distribute paper and
electronic copies of this thesis document in whole or in part in any medium now known or
hereafter created.
Signature of
Author:________________________________________________________________________
Department of Urban Studies and Planning
July 27, 2007
Certified
by:___________________________________________________________________________
William C. Wheaton
Professor of Economics
Thesis Supervisor
Accepted
by:___________________________________________________________________________
David M. Geltner
Chairman, Interdepartmental Degree Program in
Real Estate Development
1
The Impact of Climate Change on Ski Resort Operations and
Development: Opportunities and Threats
By
Daniel D. D. McGill
Submitted to the Department of Urban Studies and Planning in partial fulfillment of the
requirements for the degree of Master of Science in Real Estate Development
at the
Massachusetts Institute of Technology
September 2007
ABSTRACT
This thesis serves as a pedagogical guide to the ski resort industry, and presents a broad overview
of the unique issues that accompany climate change. The paper also provides recommendations to
resort developers as to which regions of North America will likely become desirable destination
for skiers in light of such changes.
The ski resort industry is on the cutting edge with respect to sustainable building techniques and
adoption of innovative “green” principles in day-to-day operations. But while these efforts are
admirable and set an important precedent, in the global context they do little to stem the tide of
global warming which penalizes indiscriminately. It is therefore necessary for stakeholders within
the ski industry to not only embrace adoption strategies, but also to consider what preemptive
actions can be taken to capitalize on global warming.
Using historical annual total snowfall records and “skier visit” data, this study intends to quantify
the extent to which climate change has impacted resort operations in different regions of the
United States over the last several decades. In addition, the paper provides an overview of current
and future effects of climate change on North America’s ski resort industry and provides
recommendations as to how these operators can adapt to ever changing conditions over the next
30 – 50 years. This is followed by a review of climate adaptation practices currently employed
by resort operators and stakeholders.
With few exceptions, existing literature on this topic has neglected to consider what opportunities
might emerge as a result of climate change. While the field of climatology is an ever evolving
science, the ski industry would be wise to take note as global warming is likely to prove one of
those tectonic forces that gradually – but powerfully – changes the economic landscape in which
they operate.
Thesis Supervisor: William C. Wheaton
Title: Professor of Economics
2
Table of Contents
1. Introduction............................................................................................................... 5
1.1.
Background ........................................................................................................ 7
1.2.
Future Implications ........................................................................................... 8
2. Literature Review ................................................................................................... 10
3. Methodology ............................................................................................................ 14
3.1.
Historic Climate Data Collection .................................................................... 14
3.2.
Skier Visits Data............................................................................................... 15
3.3.
Data Synthesis .................................................................................................. 16
3.4.
Future Opportunities ....................................................................................... 16
4. Global Warming Demystified ................................................................................ 18
4.1.
Overview ........................................................................................................... 18
4.3.
Greenhouse Warming ...................................................................................... 19
4.4.
Reinforcing Global Warming Mechanisms .................................................... 22
4.5.
Recent Observed Warming Trends.................................................................. 23
5. Model Results .......................................................................................................... 27
5.1.
The Regional Series Outcome:....................................................................... 27
5.1.1.
Northeast .................................................................................................. 27
5.1.2.
Southeast .................................................................................................. 29
5.1.3.
Midwest..................................................................................................... 31
5.1.4.
Rocky Mountains ..................................................................................... 33
5.1.5.
Pacific West .............................................................................................. 35
5.2.
Implications for the Future ............................................................................. 37
6. Forecast Climate Change: North America........................................................... 38
6.1.
Summary of IPCC Results............................................................................... 38
3
6.2.1.
North American Temperature ................................................................. 39
6.2.2.
Precipitation ............................................................................................. 41
6.2.3.
Snowfall, Snowpack ................................................................................. 43
7. Future Change In Regional Snowfall.................................................................... 45
7.1.
Northeast .......................................................................................................... 45
7.2.
Southeast: ......................................................................................................... 46
7.3.
Midwest............................................................................................................. 46
7.4.
Rocky Mountains ............................................................................................. 47
7.5.
Pacific West ...................................................................................................... 47
8. Adaptation and Risk Mitigations .......................................................................... 49
8.1.
Artificial Snowmaking ..................................................................................... 49
8.2.
Weather Derivatives ......................................................................................... 50
8.3.
Revenue Diversification................................................................................... 51
8.4.
Cloud Seeding .................................................................................................. 51
8.5.
Marketing ......................................................................................................... 52
9. Conclusion ............................................................................................................... 53
4
1. Introduction
With approximately 720 ski areas in North America, 475 falling within the United States, the ski
resort industry is in the midst of a veritable “Golden Age”, as a confluence of positive
circumstances has combined to advance the sport and boost revenues for entrenched operators.
These resorts range from small scale operations that service local day skiers to large destination
resorts that attract patrons from all over the world in search of the complete vacation experience.
Skiing is estimated to be a $4 billion annual industry in the U.S. and with ever increasing interest
in the sport, this figure is sure to grow.1
While professionals within the industry tend to credit this success to new innovations and clever
marketing campaigns, there are several exogenous factors outside these operators’ sphere of
influence which have propagated this good fortune.
First, demographic trends heavily favor the ski industry as the baby-boom generation transitions
into their prime leisure years. In addition the popularity of the sport continues to grow with the
echo-boomer generation (10 – 24 year olds). Additionally, with no new major resorts opened in
the last twenty-five years, the existing operators can unilaterally profit from the continued
growth. The barriers to entries are significant for new entrants, due largely to the dearth of private
lands on which to build and the challenges of obtaining government approvals to develop on
public lands. In fact, some 90% of resorts in the Pacific West and 85% of resorts in the Rocky
Mountains operate under permits administered by the United States Forest Service (USFS),
procurement of which often involves a lengthy and bureaucratic approval process.2 The absence
of new entrants enables existing operators to increase lift ticket prices with little concern of losing
their competitive advantage.
Although the future looks promising for the ski industry, there are long term threats which have
the potential to dramatically impact the business. This thesis will explore one such issue: climate
change or global warming.
In principle it is basic to understand why climate change and its resultant warming would have a
substantive impact on the ski resort industry: warmer temperatures result in shorter winters and
less snow, which directly impact the bottom line. In addition, the higher frequency of extreme
5
weather events, such as draughts and forest fires, increase the risk of costly damage to land,
infrastructure, and facilities.
Scientists’ widespread contention that global warming increases the volume of such climatic
events is supported by seemingly daily reports of weather anomalies, ranging from forest fires in
the West, to draughts in the West, and to heat waves in the Northeast. Headlines depicting Mother
Nature on a rampage have become commonplace.
To illustrate this observable fact, consider both wild fires and droughts. Wild fires pose an acute
threat to the skiing industry as ever dryer conditions continue to fuel more powerful fires which
have the potential of enveloping a resort’s carefully manicured ski slopes in a matter of days. In
addition recent studies suggest that the resulting soot released into the air lands on mountain
snowpack and leads to faster snowmelt.3
Last year alone a record 9,871,863 acres4 of forest land burned nationwide, an area greater than
the land areas of Massachusetts, Connecticut, and Rhode Island combined.5 Graph 1.1 below
illustrates the large scale of damage cause by forest fires in the U.S. over the last fifty years.
Graph 1.1: Historic Impact of Wildfires
Source: http://www.ncdc.noaa.gov/img/climate/research/2006/dec/us-wildfires-1960to2006-pg.png
6
Similarly, according to a recent study, wind-blown dust from drought-stricken and disturbed
lands can shorten the duration of mountain snow cover hundreds of miles away by up to a
month.6
1.1.
Background
Recognized as one of the most significant threats to the ski resort industry, the reality of Climate
Change is no longer in doubt. While the discourse continues regarding the magnitude and the
implications for future generations, Time Magazine recently published an article entitled
“Climate Change: Case Closed” which declares that the global warming debate is over.7 The
World Economic Forum also released a report entitled Global Risks 2007 citing Climate Change
as one of the five greatest threats to our planet.
Following are several recent examples from around the globe which highlight the timeliness of
this research:
•
The globally averaged combined land and sea surface temperature for December
2006 to February 2007 was the highest since records began in 1880;8
•
10 of the warmest winters globally since 1880 have occurred since 1995;9
•
A resort in the Alps, Abondance, at 3,051 feet, closed in July 2007 due to the chronic
absence of snow, representing the first ski resort casualty of global warming;10
•
Mountain glaciers and snow cover continue their declined in both hemispheres,
leading to sea level rise;11
•
Warming trends in Europe this winter (2006/07) prompted officials to cancel races on
the World Cup circuit;12
•
Average spring temperatures in California's Sierra Nevada range have increased more
that 2oF degrees since 1950 and if spring temperatures rise by a mere 5oF degrees on
average, California is predicted to lose 89% of its natural snow pack.13
7
Although global warming predictions vary, current weather trends in mountainous regions
indicate that appreciable effects are only just beginning to emerge. “Nationwide this year, there
were huge disparities in winter weather conditions,” said Michael Berry, president of the
Colorado-based National Ski Areas Association (NSAA), an organization which represents most
of the nation's estimated 475 ski areas.
NSAA, who publishes an annual assessment of each season entitled the Kottke National End of
Season Survey, issued the following ominous summation of the 2006/07 season in their
preliminary report:
“Estimates indicate that 2006/07 was indeed a challenging year for the ski industry.
Abnormally warm temperatures and below average snowfall impacted most areas of the
country, delaying planned openings, interrupting the season with periodic resort
closures, and otherwise shortening the effective length of the season in all regions
except the Rocky Mountains.”14
“Skier visits”, the group's measure of volume, were down by an estimated 6.9% during the
2006/07 season from the previous year,15 which amounts to a reduction of just over four (4)
million visits.
Downhill skiing is an industry that is highly dependant on particular weather variables necessary
to ensure favorable skiing conditions. Temperature and precipitation need both comply to realize
adequate snowpack and enable artificial snowmaking. Should these warming patterns persist,
many of the world's existing ski resorts may not have adequate snowpack to sustain business
operations over the next 30 – 40 years.
1.2.
Future Implications
Reviewing the latest research reports on climate change, this study will forecast which geographic
regions hold particular promise as future locations for ski operations in light of climate change.
Could Canada and/or Alaska emerge as the new hotspots for the sport’s enthusiasts?
In addition the paper will underscore strategies entrenched operators can employ today to
mitigate the risk of global warming.
8
This paper will serve as a primer for forward thinking resort developers who are considering
proactive strategies in the face of this growing concern. For example, developers should consider
taking calculated risks and place educated bets on specific promising new markets, by optioning
land in untapped areas. Owners/operators must plan for the future and think about where these asof-yet unidentified opportunities will emerge.
9
2. Literature Review
To date, there have been few studies completed which specifically examine the future impacts of
climate change on the North American downhill ski industry. The literature review did reveal a
myriad of reports on climate change generally, as well as studies examining potential effects of
climate change on various weather sensitive industries throughout the United States and Canada.
Following is a review of numerous professional and academic papers assessing both the
socioeconomic and ecological impacts of climate change, with concentrations on specific
geographic regions of the U.S.
The Michigan Journal of Economics published a paper entitled The Economic Impact of Climate
Change on the Mid-Atlantic Region’s Downhill Skiing Industry which investigates climate
change’s long-term impact on the ski industry in the Mid-Atlantic region. This report concluded
that by 2095 resort operators in this region will no longer find it financially viable to offer skiing
to their clientele. The study credits the gradual increase in temperature which will both shorten
the ski season and significantly increase operating costs, such as snowmaking.
This study went on to predict that savvy resort operators will gradually differentiate their
recreational offerings and shift to a summer/fall oriented business model focused on golf, biking,
rafting, and hiking.16
Colorado College released a report in 2006 entitled The 2006 Colorado College State of the
Rockies Report Card, which sought to predict the effect of climate change generally on the
Rockies region; including the impact on both the ecosystem and the economy. This report based
its results primarily on two discrete models, one which assumed the rise in greenhouse gas
emissions would continue unabated as they have for the past forty (40) years and another which
considers a future in which emissions are reduced considerably. While there is a clear variance in
the results between the models, both indicate upward trends in temperature, reduced snowpack,
and variations in precipitation throughout the region.17
Figure 2.1, adapted from the report, illustrates the predicted change in winter temperatures under
both scenarios. The report predicts temperatures to rise anywhere from 1.5o to 7oC depending on
the emissions output in the next eighty (80) years.
10
Figure 2.1: Winter Temperature Increase, 1976 to 2085* (Degrees Celsius)
Source: The 2006 Colorado College State Of The Rockies Report Card
Figure 2.2 reflects the anticipated loss of snowpack under both scenarios. Again, while there is a
sharp contrast between the two scenarios, both depict a future in which snowfall is diminished.
Figure 2.2: April 1 Snowpack Change, 1976 to 2085* (centimeters of Snow Water Equivalence)
Source: The 2006 Colorado College State Of The Rockies Report Card
Finally, Figure 2.3 shows the forecast change in precipitation under both scenarios. The report
predicts an increase throughout much of the Rockies in higher latitude regions. Much of this
increase will manifest itself as rain however, negatively impacting ski resorts in those regions.
11
Figure 2.3: Annual Precipitation Change, 1976 to 2085* (Centimeters Per Year)
Source: The 2006 Colorado College State Of The Rockies Report Card
The report went on to summarize the predicted impact on tourism stating that “a change in
climate will undoubtedly impact the tourism industry in the Rockies, a region often seen as the
nation’s playground.”
The State Of The Rockies Report forecasts dramatic reductions in snowpack in counties which
house some of the Rockies’ largest ski areas. Most ski counties in Colorado are predicted to lose
around 50%. The report identifies the northern region of the Rockies, such as Teton County,
home to Jackson Hole, as the least impacted, with only 26% projected reduction in spring
snowpack. 18
An additional paper which is uniquely apropos considering today’s headlines, is entitled Wildfires
in the West (S.W. Running et. al., 2006) and chronicles the ever growing risk of fire in the
western United States. This report finds that although land-use history is an important factor in
wildfire risk, the broad-scale increase in wildfire frequency across the western United States is
primarily driven by increased spring and summer temperatures coupled with earlier spring
snowmelt which leads to extended fire seasons. The team also discussed how increased biomass
burning will result in a carbon release from forest ecosystems thereby potentially turning western
forests from net users of carbon dioxide to net contributors of the gas. This could have large scale
12
implications for the terrestrial carbon cycle in the United States, since western forests are
currently responsible for 20 to 40% of total U.S. carbon sequestration.19
Another comprehensive report is Aspen Global Change Institute’s Climate Change and Aspen:
An Assessment of Impacts and Potential Responses. The City of Aspen has consistently been on
the forefront of the “Green Movement” and this 2006 assessment is the result of their extensive
efforts to draw attention to climate change. The report begins with a thorough review of current
trends in climate and then goes on to consider possible future climates. The institute took a threepronged approach which modeled future scenarios with low, medium, and high levels of future
greenhouse gas.
Climate models from several major climate centers were utilized to project changes in monthly
temperature and precipitation by 2030 (near term) and 2100 (long term).20 The results of the
climate modeling were then used to examine how variations in climate will affect both Aspen’s
socioeconomic well being and the diverse ecosystem. The report concludes with a discussion of
the primary regional stakeholders and actions they can undertake in response to forecast changes.
13
3. Methodology
This dissertation intends to quantify the extent to which climate change has impacted resort
operations in different regions of the United States over the last several decades, using both
historical annual total snowfall data and “skier visit” data to evaluate the impact.
The term “skier visit”, is defined as “one person visiting a ski area for all or any part of a day or
night for the purpose of skiing, snowboarding, or other downhill sliding. Skier visits include fullday, half-day, night, complimentary, adult, child, season pass, and any other type of ticket that
gives a skier/snowboarder the use of an area’s facilities.”21
For this paper, the thesis will consider five (5) primary ski regions: Pacific West, Rocky
Mountain, Midwest, Northeast, and Southeast. These regions are illustrated in Exhibit 3.1 below.
Figure 3.1: United States Ski Regions
Source: NSAA: National Ski Areas Association
3.1.
Historic Climate Data Collection
Data was collected on both historic annual mean temperatures and historic annual snowfall
accumulation. This data was sourced from numerous representative weather stations in each of
14
the five predefined geographic regions. These stations were selected on the basis of their general
proximity to ski areas, their elevation, and the quality of the data available. To ensure the
integrity of the data, there were numerous stations evaluated and subsequently eliminated from
the study due to incomplete data or to their locations exhibiting different climatological
characteristics. Only stations with >95% complete records of snowfall were used.
The weather stations are a part of the United States Historical Climatology Network (USHCN),
an organization which maintains a high quality data set of basic meteorological variables from
over 1,000 observing stations across the 48 contiguous states. The data aggregated by USHCN
includes observations of maximum and minimum temperature, precipitation amount, snowfall
amount, and snow depth. Data records extend through 2005 and are essentially complete for at
least 50 years; the latest beginning year of record is 1948.22
The temperature data was derived using monthly averages collected from stations across the
country. Annual snowfall data, on the other hand, is not provided as monthly figures, rather as
daily records. Therefore the thesis collected and summed these daily records - often spanning
100+ years – for each USHNC station.
3.2.
Skier Visits Data
Next, in order to analyze and compare the average annual performance of resorts; “skier visit”
data was collected from each region. “Skier visit” figures are a widely accepted measure of expost demand and business success in any given year.
There are two methods whereby to secure this data; (1) by reaching out to each resort on an
individual basis or (2) by turning to one of the ski trade associations that aggregate these figures
and statistics. Preliminary attempts to secure this data directly from a number of resorts proved
time consuming and ineffective as privately owned resorts are uniformly guarded with these
figures. Meanwhile publicly held ski resorts report lift ticket sales in their Annual Report as a
percentage of revenue rather than as discrete “skier visits” figures.
Consequently the second method was used and the study employed statistics as reported by the
National Ski Area Association (NSAA), an association consisting of ski area owners and
operators. NSAA is the principle ski trade association which collects and published a wide series
15
of industry information collected from members accounting for more than 90% of the
skier/snowboarder visits nationwide.23
3.3.
Data Synthesis
Upon completion of data collection, the thesis employed a diagnostic VAR model designed to
interpolate the correlation between weather in any given year and the performance of resorts in
that region, as measured by skier visits in the corresponding year. The intent is to determine
whether there is a tendency for regions to struggle during low snowfall seasons and, if so,
determine the magnitude of this response.
Clearly there are a wide variety of variables that influence skier decision making patterns in any
given season. This study will attempt to establish a relatively simple correlation between snowfall
and skier visits, which will support the proposition that this industry is uniquely susceptible to
climate change and the resultant loss of snowpack.
Using the model, the thesis will determine the future impacts and change in skier visits based on
forecasts reductions in snowfall in each region.
3.4.
Future Opportunities
Next the thesis takes a broad-brush perspective on the North American ski industry by
concentrating on high-level climate forecasts for the continent. While there are statistical
downscaling techniques available to draw relationships between large-scale global climate model
(GCM) data and smaller scale climate variables at a specific location, there are significant
shortfalls to these techniques as they assume that the statistical relationship between the climate
variables in a GCM and observed climate at a specific location will not change with climate
change. This assumption of a constant statistical relationship has been challenged and is likely to
yield inaccurate results; therefore the thesis will not employ these techniques.24
To accomplish this, the study identified geographic regions which will likely emerge as attractive
locations for resort development due to climate change. These predictions will be based primarily
on the latest report issued by the Intergovernmental Panel on Climate Change (IPCC), released in
February 2007.
16
Established in 1988 by two UN agencies, the IPCC is widely recognized as the world’s foremost
authority on climate change. The IPCC issued comprehensive assessments in 1990, 1996, and
2001; and its Fourth Assessment Report (AR4) is the most comprehensive synthesis of climate
change science to date. The report aggregates studies contributed by the world’s foremost
climatologists from over 130 countries and represents six years worth of work. More than 450
lead authors have received input in excess of 800 contributing authors, and an additional 2,500
experts reviewed the draft documents.
The thesis will evaluate the conclusions from the AR4 report and extrapolate from the North
America climate change projections which areas are likely going to become more temperate
and/or benefit from an increase in overall annual snowfall levels.
To date, nearly all rigorous research has centered on measuring the effects of global warming and
strategies to stem the tide. This section will put a new – positive – slant on global warming and
survey what new regions might benefit and become attractive resort destinations. Research could
pinpoint Canada and/or Alaska as locales which will realize significant booms to their tourist
industries.
17
4. Global Warming Demystified
While the scope of this thesis is fundamentally regional in natural and focused on a specific
graphic area, it is necessary to understand the anatomy of global climate change. What follows in
this section is a brief yet concise explanation of the global warming phenomenon.
4.1.
Overview
Historically speaking it is not unusual for temperatures to vary widely year to year, week to week
or even day to day. By utilizing a variety of techniques, such as observing marine sediments and
drilling polar ice cores, historic weather records going back hundreds of thousands of years can
be collected and analyzed.
These natural data warehouses confirm that long-term variations of climate conditions are a
completely natural. These variations occur in accordance with the variation, distribution and
magnitude of solar radiation, which are further amplified by ocean-land-atmosphere
interactions.25 However, the swift temperature increase observed in the past half century cannot
be fully explained by these natural influences.
The latest report released by the Intergovernmental Panel on Climate Change (IPCC) concludes
that “it is extremely unlikely (<5%) that the global pattern of warming during the past half
century can be explained without external forcing, and very unlikely that it is due to known
natural external causes alone. The warming occurred in both the ocean and the atmosphere and
took place at a time when natural external forcing factors would likely have produced cooling.
Greenhouse gas forcing has very likely caused most of the observed global warming over the last
50 years.”26 In other words, mankind has caused global warming.
4.2.
Climate Defined
Vital to any discussion of global warming (climate change) is developing a working knowledge
of the sophisticated system that comprises the earth’s climate. IPCC defines climate as “a
complex, interactive system consisting of the atmosphere, land surface, snow and ice, oceans and
other bodies of water, and living things. The atmospheric component of the climate system most
obviously characterizes climate; climate is often defined as ‘average weather’. Climate is usually
18
described in terms of the mean and variability of temperature, precipitation and wind over a
period of time, ranging from months to millions of years (the classical period is 30 years).”27
The climate system evolves over time in response to both its own internal dynamics as well as
external factors known in the scientific community as ‘forcings’.28 These ‘forcings’ can occur
naturally such as volcanic eruptions and solar variations and can also be the result of
anthropogenic actions, particularly through the creation of greenhouse gases.
The Earth’s climate is powered by solar radiation and can be altered in three basic ways. First and
most basic is a change in the magnitude of incoming solar radiation by either change in Earth’s
orbit or variation in the Sun itself. Next is by a reduction in the “albedo” effect, or the fraction of
solar radiation that is reflected back into space by the planet’s numerous reflective surfaces, such
as glaciers and bodies of water.29 And finally, climate is vulnerable to the introduction of new
pollutants, or greenhouse gases, into the atmosphere which traps heat emitted by the planet.
4.3.
Greenhouse Warming
“Greenhouse warming” and the resulting “greenhouse effect” are terms used to explain the rise in
global temperatures over the last many decades. Following is a short explanation of the
phenomena.
As the principal source of warmth on Earth, the sun emits approximately 340 watts per square
meter (w/m2) of radiant energy (the precise figure varies over time, by +/- 0.1%)30. As it enters
the Earth’s atmosphere, this energy, transferred via “short wavelength” radiation, is not
appreciably hindered by greenhouse gases, which are mostly translucent to “short wavelength”
radiation. However, of the 340 w/m2 the sun emits, only about 240 w/m2 is absorbed by the
Earth’s surface. The remaining 100 w/m2 is reflected off clouds, assorted aerosols, and various
reflective features of the planet such as snow and ice.
To balance this incoming energy, the Earth itself must radiate, on average, the same amount of
energy back into space. However, the radiation emitted from the earth is less energetic and
transferred via “long wavelength” radiation, or “terrestrial radiation”.31 Everything on Earth
emits terrestrial radiation continuously. That is the heat energy one feels radiating out from a fire;
the warmer an object, the more heat energy it radiates. To emit 240 w/m2, a surface would have to
19
have a temperature of around -19°C (-2oF). This is much colder than the conditions that actually
exist at the Earth’s surface (the global mean surface temperature is about 14°C or 57oF). Instead,
the necessary (-19°C) is found at an altitude about 5 km above the surface.32
The reason the Earth is not unbearably cold (-19°C ) is the presence of “greenhouse gases” in the
atmosphere which, although transparent to the sun’s short wavelength energy, are somewhat
opaque to long wavelength radiation and serve to prevent terrestrial radiation from escaping the
atmosphere, redirecting nearly half of it, roughly 180w/m2, back down to Earth. This redirection
of energy is what is commonly known as the “natural greenhouse effect”. (see Figure 4.1)
Figure 4.1:
Illustration of the Greenhouse Effect
Source: IPCC, Fourth Assessment Report "Climate Change 2007", pg. 115
This greenhouse effect is both a natural and beneficial process. The earth emits greenhouse gases
in large number of ways: such as through volcanoes, the decay and respiration of plant material,
forest fires, animal digestive processes, wetlands, and natural soil and ocean processes. These
gases work to regulate the world’s temperature and keep the planet inhabitable by human beings
who can only tolerate a relatively narrow range of temperatures.
20
The most important greenhouse gases present in the Earth’s atmosphere are water vapor and
carbon dioxide. (Nitrogen and oxygen, the most prevalent gases, have no such impact on
terrestrial radiation). 33 As Figure 4.2 illustrates, the correlation over the past 400,000 years
between CO2 and temperature is striking and undeniable, the two trend lines are virtual reflections
of one another providing clear evidence of the direct relationship.
Figure 4.2:
Historic Carbon Records and Temperature Records
Source: Petit, J.R. et al. (1999), ‘Climate and Atmospheric History of the past 420,000 Years from the
Vostok Ice Core, Antarctica’, Nature, 399, pp. 429-436.
Over the past 150 years, however, the “natural” rate and quantity of greenhouse gases cycling
from the Earth, into the atmosphere, and back to the Earth has been greatly exacerbated by
humankind. Since the Industrial Revolution, excessive levels of these gases have been produced
and released into the atmosphere at a level far exceeding any “naturally occurring” rate. In recent
decades, stemming from the Industrial Revolution, humankind has dramatically altered the
chemical composition of the atmosphere with the introduction of manufactured pollutants which
have served to intensify the greenhouse effect. Activities, including fossil fuel combustion,
fertilizer and manure application, biomass burning, and soil cultivation have resulted in increased
concentrations of carbon dioxide by about 30% (Table 4.1). Methane concentrations have risen
by nearly 150% and nitrous oxide concentrations have increased about 15%.
21
Table 4.1: Historic Concentrations
Greenhouse Gas
Carbon Dioxide (ppm)
Methane (ppm)
Nitrous Oxide (ppm)
Preindustrial Atmosheric
Concentrations
1998 Atmosheric
Concentrations
278
0.7
0.27
365
1.745
0.314
Source: U.S. Greenhouse Gas Inventory Program, Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2000. U.S. Environmental Protection Agency (2002)
4.4.
Reinforcing Global Warming Mechanisms
What has been observed in the past 50+ years is the genesis of a “self-reinforcing cycle” of
warming. While scientists continue to debate the extent of this phenomenon, recent studies
strongly suggest that global warming does feed on and sustain itself.
Although the long run history of Earth’s mean temperature is indicative of a system that is meanreverting, when excessive amounts of terrestrial radiation is captured in the Earth’s atmosphere
artificially, the climate system adjusts accordingly. Many scientists postulate that the now warmer
Earth responds by emitting even more terrestrial radiation. This, in turn, increases the amount of
radiation remaining in the earth’s atmosphere and continues the warming cycle.
Below are several examples of this “positive feedback” mechanism:34
1.
Melting of the permafrost, which exposes organic matter that then decays,
releasing the greenhouse gases methane and carbon dioxide;35
2.
As the atmosphere warms, the amount of water vapor it can hold rises. Because water
vapor is an active greenhouse gas, this multiplies the effect of warming;
3.
Rising temperatures and changes in weather patterns, particularly rainfall, are thought to
damage the ability of the Earth’s natural “sinks” – the oceans and soil – to absorb
CO2;36
22
4.
As snow and ice gradually melt and dissipate the leave behind darker land and
surfaces which absorb more of the Sun’s heat, causing more warming, which causes more
melting, and so on, in a self-reinforcing cycle;37
5.
Furthermore, ocean acidification, the result of dissolved CO2, weakens the CO2
absorption organisms.
While debate in the scientific community continues over the “feedback mechanism” theory, these
events likely play a significantly larger role in global warming than previously estimated. These
revelations have prompted many scientists to revisit previous studies and adjust their estimates.38
4.5.
Recent Observed Warming Trends
Today, there is widespread consensus that near-surface air temperatures are increasing.
According to the IPCC, over the 20th century, the global average surface temperature has
increased by about 0.6ºC (1.08oF). The year 2005 was reported as having been the warmest year
in several thousand years and 2007 is expected to break that record.39 It’s worth noting that the
record warmth recorded in 2005 is even more unusual as it was not aided by a tropical El Niño
incident. Whereas the prior record year, 1998, was enhance 0.2°C above the trend line by the
strongest El Niño of the past century.40
The Center for Climate Change and Environmental Forecasting performed a study that tracked
warming over the past 100+ years. The results of this study are illustrated below (Figure 4.3) on
the globally-averaged mean annual temperature time series which includes both land and ocean
data point for 1880-2000. Although yearly and decadal variations are clearly visible, the 19012004 long-term trend in combined land and ocean temperatures is consistent with IPCC’s
conclusion at approximately +0.6°C/century.41
The study concludes that land surface temperatures have increased at a rate of +0.8°C/century
while ocean surface temperatures have risen +0.6°C/century during the same time period. The
trend has increased to +0.17°C/decade (.17oF) during the past 25 year period (1979-2004) when
considering combined land and ocean temperatures.
23
Figure 4.3. Global near-surface temperatures for land, ocean, and combined land and ocean
Source: http://www.ncdc.noaa.gov/oa/climate/research/trends.html
In another large-scale exercise, Mann et al. (1998, 1999) used historical data from tree rings, ice
cores, and other ‘proxies’ to reconstruct the northern hemisphere’s mean temperature over the
past 1,000 years. This resulted in the ‘hockey stick’ chart (Figure 4.4) which reflects a dramatic
positive shift in temperatures over the last 30 years or so.
24
Figure 4.4: Northern Hemisphere’s Mean Temperature over the past 1,000 years
Source: Intergovernmental Panel on Climate Change (2001), vol.II, Summary for Policy Makers.
While this study and its results prompted heated debates when it was released, the conclusions are
now widely accepted by most scientists, including, importantly, by a specially convened
committee of the US National Academy of Sciences. The committee's chair is reported as saying
that it has a “high level of confidence” that the second half of the 20th century was warmer than
any other period in the past four centuries.42
Another study, completed by NASA, focused on the past 125 years relied mainly on instrumental
data to evaluate global warming. Below are graphs from this study which reflect both general
global warming trends (Figure 4.5) and further localizes the results to graphically illustrate both
Northern and Southern Hemispheres independently over the period (Figure 4.6).
25
Figure 4.5: Global Annual Mean Surface Air Temperature Change
Source: NASA Goddard Institute for Space Studies website, Jan. 2007
Figure 4.6: Annual Mean Temperature Change for Hemispheres
Source: NASA Goddard Institute for Space Studies website, Jan. 2007
26
5. Model Results
In order to determine whether ski resort returns have generally suffered as a result of climate
change historically, econometric analyses were engineered to run a “skier visit” series for each of
the five regions: Pacific West, Rocky Mountain, Midwest, Northeast, and Southeast.
These series considered annual skier visits in each region and quantified their correlation
to annual snowfall accumulation, the independent variable used to signify climate change
in the model. The variables are defined below:
Variable
Definition:
SV:
Skier Visits
SF:
Snowfall
The results were fairly predictable. First, resorts which depend on heavy weekend traffic from
dense urban areas, predominately areas along both coasts exhibit more sensitivity to natural
snowfall accumulation than those resorts in central regions of the country. This is consistent with
prior studies which conclude that the Northeast and the Pacific West regions are more susceptible
to varied conditions due to their reliance on weekend visits by patrons who can spontaneously
change/cancel plans in the event of marginal conditions.
Meanwhile, ski vacations booked in the Rocky Mountain region, for instance, customarily require
planning and investment long before any snowfall forecasts can be issued. This fact coupled with
visitors’ propensity to align ski vacations with inflexible work and school schedules, results in
skiers proceeding with scheduled trips, conditions notwithstanding.
5.1.
The Regional Series Outcome:
5.1.1.
Northeast
The weather stations selected to represent snowfall in this region were both located in Vermont.
The decision to use two (2) stations was predicated on the quality and consistency of data
available for both, coupled with their proximity to ski resorts. The first, Cavendish, is located
approximately 6.5 miles from both Okemo Resort and Ascutney Mountain. The next station,
27
Cornwall, is approximately 20 miles from both Mad River Glen and Sugerbush and exhibits
consistent geographic characteristics.
The results from the Northeast time-series (Table 5.1) reflect a modest (positive) correlation
regionally between total annual snowfall and skier visits. For every one hundred (100) additional
inches of snowfall, an additional 1.52 million skier visits are anticipated, resulting in a 14%
increase. While this is a notable percentage increase, it’s important to keep in mind that the
regional average snowfall is only 98 inches; hence an additional 100 inches of snow would
constitute a record breaking year.
Table 5.1: Northeast – Skier Visits and Annual Snowfall Totals
Northeast Skier Visits vs. Annual Snowfall
Regression Statistics
Multiple R
0.455493557
R Square
0.207474381
Adjusted R Square
0.175773356
Standard Error
1.404501447
Observations
27
Skier Visits = 10.68 + 0.0152 SF
ANOVA
df
Regression
Residual
Total
Intercept
Annual Regional
Snowfall (inches)
1
25
26
SS
12.9102769
49.31560784
62.22588474
MS
12.9102769
1.972624314
F
6.544721572
Significance F
0.016960755
Coefficients
10.68002051
Standard Error
0.692639119
t Stat
15.41931464
P-value
2.80879E-14
Lower 95%
9.253503555
0.015189988
0.005937612
2.558265344
0.016960755
0.002961246
Figure 5.1 is a graphical depiction of natural snowfall against skier visits for the period 1978 2005. During the early 90’s there was a dramatic increase in snowfall, to which skier visits
respond in kind. However there is a stark disconnect between total snowfall and visits occurring
between 1985 and 1988. With the exception of this anomaly, the trend in skier visits corresponds
with plentiful snowfall as is discernible during the seasons of 1993, 1995, and 2002.
28
Figure 5.1: Northeast Data
Skier Visits (million)
Annual Regional Snowfall (inches)
16
250.00
14
200.00
10
150.00
8
100.00
6
Snowfall (inches)
Skier Visits (millions)
12
4
50.00
2
0
0.00
1978
5.1.2.
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Southeast
To approximate snowfall for the Southeast region, annual data was averaged from four (4)
stations which returned complete data sets and were within close proximity of local resorts. Two
stations were located close to Ski Denton in northwestern Pennsylvania, with one located in
western Maryland, very close to western Maryland’s Wisp resort. The last station is located in
West Virginia and is within 15 miles of both Canaan Valley and Timberline Four Seasons.
The results of the regression analysis are below (Table 5.2):
29
Table 5.2: Southeast – Skier Visits and Annual Snowfall Totals
Southeast Skier Visits vs. Annual Snowfall
Regression Statistics
Multiple R
0.286986494
R Square
0.082361248
Adjusted R Square 0.045655698
Standard Error
0.631884335
Observations
27
Skier Visits = 4.22 + 0.0107 SF
ANOVA
df
Regression
Residual
Total
Intercept
Annual Regional
Snowfall (inches)
1
25
26
SS
MS
0.895914076 0.895914076
9.981945331 0.399277813
10.87785941
Coefficients Standard Error
t Stat
4.22040915 0.482510606 8.746769698
0.01068637
0.007134025 1.497944045
F
Significance F
2.243836363
0.14666899
P-value
4.44645E-09
Lower 95%
3.226659963
0.14666899
-0.004006429
Although slight, the model reveals a positive correlation between snowfall and skier visits. Per
these results, an additional fifty (50) inches of snowfall would translate to approximately 534,000
additional skier visits, which represent a 12.7% bump in expected business. Again, it’s necessary
to point out that the average snowfall for the Southeast if only 66 inches, therefore an increase of
50 inches would be a banner year for this region.
Figure 5.2 shows natural snowfall against skier visits for the Southeast during the period 1978 2004. Here the endogenous variable does not appear to mirror snowfall data, as there is a clear
disparity in both 1980 and 2000 when increases in snowfall result in reductions in skier visits.
Resorts in this region are characterized by their strong dependence on artificial snowmaking,
which allows them to offer reliable conditions in spite of lackluster snowfall, insulating them
against dry seasons.
30
Figure 5.2: Southeast Data
Skier Visits (million)
Annual Regional Snowfall (inches)
7
120.00
6
100.00
5
4
60.00
3
40.00
2
20.00
1
0
0.00
Year
5.1.3.
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Midwest
The Midwest region was represented by two (2) stations which were again proximate to local ski
resorts and had rich data sets available. Minocqua Dam is located in northern Wisconsin and is
approximately 20 miles north of Camp 10, a small scale resort serving northeast Wisconsin. The
other station, Ironwood, is located in the northwest panhandle of Michigan roughly 6 miles from
Whitecap Mountain, a resort in northern Wisconsin.
The Midwest regression analysis (Table 5.3) results denote a statistically insignificant correlation
between snowfall and skier visits. This lack of connection is not entirely unexpected for this
region which is characterized by small family oriented resorts. One hypothesis is that the weather
conditions which deliver such heavy snowfall are harsh and serve to dissuade families that are in
search of more inviting conditions. The numbers of would-be patrons that opt to stay home serve
to offset the gains in visits one would expect due to heavy snowfall.
31
Snowfall (inches)
Skier Visits (millions)
80.00
Another explanation could be that the region effectively shuts down in response to large amounts
of snowfall, as local infrastructure is simply not able to handle the burden, thus stymieing
transportation.
Table 5.3: Midwest Data
Midwest Skier Visits vs. Annual Snowfall
Regression Statistics
Multiple R
0.0602204
R Square
0.0036265
Adjusted R Square -0.0362284
Standard Error
0.7907522
Observations
27
Skier Visits = 7.41 - 0.00132 SF
ANOVA
df
Regression
Residual
Total
Intercept
Annual Regional
Snowfall (inches)
SS
0.056896577
15.63222594
15.68912252
MS
0.056896577
0.625289038
F
Significance F
0.090992443 0.765414239
Coefficients Standard Error
7.410625 0.677733847
t Stat
10.93441777
P-value
Lower 95% Upper 95% Lower 95.0%
5.13034E-11 6.014806044 8.806444 6.014806044
1
25
26
-0.0013248
0.004391842
-0.301649537
0.765414239 -0.01036997 0.0077204
-0.01036997
Figure 5.3 provides an illustration of Midwest skier visits and snowfall totals data. This chart
displays the absence of really any contemporaneous relationship between the two. The
endogenous variable simply does not respond to relatively dramatic swings in the exogenous
variable. These results are indicative of a region in which snowpack is dependable and ski
operators are less vulnerable to variations in snowfall.
32
Figure 5.3: Midwest – Skier Visits and Annual Snowfall Totals
Skier Visits (million)
Annual Regional Snowfall (inches)
12
250.00
10
8
150.00
6
100.00
4
50.00
2
0
0.00
Year
1979
5.1.4.
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Rocky Mountains
As the preeminent ski destination in the United States, if not all of North America, the Rocky
Mountain region has earned an international reputation for its steep vertical drops and deep
snowpack. Resorts in this region are also more challenging to reach, a characteristic which works
to the local ski industry’s advantage.
After evaluating weather station data from Montana, Wyoming, and Utah, two (2) representative
stations in Colorado were selected. The Dillon and Steamboat Springs stations both provided the
best data and closely proximate the regional snowfall trends. The Dillon station is roughly 15
miles from Vail/Beavercreek, while the Steamboat Springs station is located at the resort which
bears its name.
As the results below indicate (Table 5.44), snowfall does not determine the magnitude of demand
in the Rockies. If in a given year the region received a hundred (100) additional inches of snow,
the model predicts no concomitant shift in skier demand. This is a consequence of the significant
33
Snowfall (inches)
Skier Visits (millions)
200.00
time and capital investment required to arrange travel to the Rocky Mountain region. Also, these
resorts are fully prepared for periods of marginal snowfall and therefore visits do not diminish.
Table 4: Rocky Mountain Data
Rocky Mountain Skier Visits vs. Annual Snowfall
Regression Statistics
Multiple R
0.109248093
R Square
0.011935146
Adjusted R Square
-0.027587448
Standard Error
1.876175563
Observations
27
Skier Visits = 17.94 - 0.0048 SF
ANOVA
df
Regression
Residual
Total
Intercept
Annual Regional
Snowfall (inches)
SS
MS
1.062990141 1.062990141
88.0008686 3.520034744
89.06385874
F
0.301982855
Significance F
0.587517895
Coefficients Standard Error
t Stat
17.93843527 1.212224319 14.79795034
P-value
7.12232E-14
Lower 95%
15.44181257
-0.004757218
0.587517895
-0.022586418
1
25
26
0.008656891 -0.549529667
Figure 5.4 illustrated these results with a graph depicting a trend of steadily increasing skier visits
that is segregate from the effects of snowfall. This was evident in Utah this year, where the state
reported a record-breaking year for business in spite of lackluster snowfall. Carolyn Daniels,
spokeswoman for Powder Mountain, reported that while a relatively lean year for snow prevented
some locals from coming to the mountain, visitors from out of state more than made up for the
shortfall.43
34
Figure 4: Rocky Mountains – Skier Visits and Annual Snowfall Totals
Skier Visits (million)
Annual Regional Snowfall (inches)
25
300.00
250.00
200.00
15
150.00
10
Snowfall (inches)
Skier Visits (millions)
20
100.00
5
50.00
0
0.00
Year
5.1.5.
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Pacific West
The Pacific West is the final region considered in this study and encompasses California,
Washington, Oregon, Nevada, as well as other states. Gathering complete data for this region
proved challenging as numerous weather stations with complete data sets were situated at lower
elevations and therefore reported extended periods of insignificant snow accumulation.
Consequently, after consulting with various industry professionals, the data utilized here is from
one station, Tahoe City, which is proximate to several renowned California resorts and serves as
an appropriate proxy for the region.
While the correlation between visits and snowfall is relatively minor, the model (Table 5.5) does
generate a positive response to increased snowfall. This supports the theory that skiers in this
region are more apt to spontaneously travel to the resorts during periods of superior snowfall.
Specifically, the model calculates an approximately 850,000 uptick in skier visits in response to
an additional hundred (100) inches of snowfall during a given season.
35
Table 5.5: Pacific West Data
Pacific West Skier Visits vs. Annual Snowfall
Regression Statistics
Multiple R
0.460015621
R Square
0.211614372
Adjusted R Square
0.180078947
Standard Error
0.970828735
Observations
27
Skier Visits = 8.97 + 0.0081 SF
ANOVA
df
Regression
Residual
Total
1
25
26
SS
MS
6.324580347 6.324580347
23.56271084 0.942508434
29.88729119
Coefficients Standard Error
t Stat
8.97301622 0.578669407 15.50629101
Intercept
Annual Regional
Snowfall (inches)
0.008125742
0.003136822 2.590438193
F
Significance F
6.710370032
0.015765177
P-value
2.47182E-14
Lower 95%
Upper 95%
7.781224277 10.164808
0.015765177
0.001665337 0.0145861
Figure 5.5 is the chart reflecting the data trends for Pacific West. A trend is observable over the
thirty year period in which skier visits relate to snowfall totals. This relationship is most
pronounced in the years between 1981 and 1984 where the variation in the endogenous variable,
skier visit, closely mirror the patterns of snowfall. One can also observe a similar pattern over the
last decade, with skier visits lagging snowfall ever so slightly.
Figure 5.5: Pacific West – Skier Visits and Annual Snowfall Totals
Annual Regional Snowfall (inches)
350.00
12
300.00
10
250.00
8
200.00
6
150.00
4
100.00
2
50.00
0.00
0
Year
1979
1981
1983
1985
1987
1989
1991
36
1993
1995
1997
1999
2001
2003
Snowfall (inches)
Skier Visits (millions)
Skier Visits (million)
14
5.2.
Implications for the Future
While the limited VAR model used in this study does not attempt to account for the many unique
variables that come into consideration when decisions whether to ski are made, it is important to
recognize the straightforward relationship between resorts’ success and climate conditions.
Coupled with today’s most advanced climate modeling technology, a greater understanding of
future consequences for the ski industry will help guide mitigation strategies and encourage
developers to look towards the future and begin considering where new opportunities will
surface.
37
6. Forecast Climate Change: North America
Over the next 30 to 50 years, as the global climate continues to warm, many people and nations
will find themselves in possession of land and resources of rising value, while others will suffer
dire losses and be left with desiccated property unfit for everyday life. Economic change means
winners as well as losers. Huge sums will be made and lost as the global climate changes.44
The natural question arises of exactly which regions of North America will benefit from milder
winters and which areas will lose. Using the most sophisticated models available, this section will
provide a broad-brush summary of the forecast climate changes in the United States and discuss
the implications of a warming world.
6.1.
Summary of IPCC Results
The IPCC report offers a sobering assessment of the impacts of climate change in North America
during the coming century. As the summation of twenty-one (21) distinct models from scientists
around the world, the report provides a range of potential future outcomes, each with varying
degrees of confidence.
By closely examining the effective illustrations – maps and graphics – within the report, the thesis
extrapolated conclusions about future changes.
Globally, all 21 models represented in the IPCC report, project a steady increase in mean surface
air temperature (SAT) throughout the 21st century. This change is caused by increases in
anthropogenic greenhouse gas emissions and the associated radiative heating that follows.
The 21 IPCC models take into account varying levels of future greenhouse gas (GHG) emissions.
Therefore different conclusions are drawn. The author of this thesis consulted with Professor
Peter Stone, a Harvard Ph.D. in Applied Mathematics (1964) and, most recently, Director of the
MIT Climate Modeling Initiative (1995-2004), to determine upon which model the study should
base its conclusions. Based on Professor Stone’s feedback, the thesis will focus on model “A1B”,
which uses moderate levels of GHG emissions as its input. This is considered by Professor Stone
to be the most accurate depiction of future climate change.
38
Additionally Professor Stone and his team provided their forecast of global increases over a 30
year timeframe. The projected increases in global mean surface temperature from the decade
2002-2011 to the decade 2032-2041 and their respective confidence intervals follows:45
−
80% confidence interval: 0.78oC to 1.06oC (1.4oF – 1.91oF)
−
90% confidence interval: 0.72oC to 1.18oC (1.33oF – 2.12oF
Figure 6.2 below shows the forecast increases in global temperatures relative to the average
temps of 1980 to 1999. Observe that the A1B model calculates a range of 1.8oC - 2.0oC (2.25oF –
2.6o F) increase over the next half century.46
Figure 6.2: Forecast surface warming for scenarios A2, A1B and B1. Lines show the multi-model
means, shading denotes the ±1 standard deviation range of individual model annual means.
Source: IPCC Fourth Assessment, 2007. pg. 762
6.2.
North America Climate Change Projections
6.2.1.
North American Temperature
The IPCC report deduces that all of North America is very likely to warm during this century
and states that the annual mean warming is going to exceed the global mean.47
39
In northern regions of the continent, warming is likely to be most pronounced during the
winter months, which will have a direct and negative impact on winter snowpack.48
The report goes on to state that the lowest winter temperatures are likely to increase more than
the average winter temperature in northern North America; in other words, the coldest and
harshest days of winter will realize the most change, which could be a positive by reducing the
number of unskiable days due to adverse conditions.
Figure 6.3 below displays Alaska and Northern Canada respectively. The are the regions
where the largest warming trends are projected to occur. The simulations reports as much as a
10oC (18oF) temperature increases in these regions by 2100 due primarily to the positive
feedback resulting from a reduction in snow cover, or ablation.
Figure 6.3: Temperature trends in Alaska and Northern Canada for 1906 to 2005 (black line); and as
projected for 2001 to 2100 by models for the A1B scenario (orange envelope). The bars at the end of
the orange envelope represent the range of projected changes for 2091 to 2100. The A1B scenario is
represented by the middle bar.
Source: IPCC, Fourth Assessment, 2007. pg. 889
This prediction of considerable warming in those areas characterized today by harsh and frigid
weather, carries with it great promise for future ski resort development opportunities. Alaska,
British Columbia, and Alberta all lay claim to promising peaks which will benefit from warmer
temperature and increased snowfall. Several examples follow.
Today, Alaska’s largest ski mountain, Alyeska, located some 40 miles southeast of Anchorage
boosts on average some 782 inches of snow a year. The summit is 4,000 feet, with a rise of 2,500
40
feet. There are 1,000 skiable acres; 89 % of which is for intermediate or advanced use. The
popularity of this area will continue to gain as climate change makes conditions more desirable.49
In January 2007, Intrawest Corporation announced plans to develop Mt. Mackenzie, a remote
peak about 175 miles (5 hours) east of Calgary. “Revelstoke”, as it’s known, will have 115 runs,
21 lifts, and a vertical drop of 1,829 meters (2,719 ft), the longest in North America. Capital
investment is expected to surpass $1 billion50.
Figure 6.4 represent Western and Central North America respectively and reflects warming
trends which will impact the majority of ski resorts in the United States and Canada. On an
annual-mean basis, surface air temperature are projected to warm from 2°C to 3°C (3.6°F to
5.4°F) along the western, southern and eastern borders of the continental over the next century.
The northern regions are expected to realize an increase of more than 5°C (9°F).
Figure 6.4: Temperature trends for Western and Central North America for 1906 to 2005 (black
line); and as projected for 2001 to 2100 by models for the A1B scenario (orange envelope). The bars
at the end of the orange envelope represent the range of projected changes for 2091 to 2100. The
A1B scenario is represented by the middle bar.
Source: IPCC, Fourth Assessment, 2007. pg. 889
6.2.2.
Precipitation
When considering precipitation, the report envisages varied changes across North America.
Generally global warming is expected to be accompanied by an increase in annual mean
precipitation over much of the continent with the largest increase believed to occur during the
winter months in the greater Northeast regions. The increase is projected to be as much as 30%
41
(Figure 6.5) which will effect the ski operations in Canada and those located in the northeastern
region of the United States.
IPCC does indicate likely decreases in precipitation in the southwestern region of the United
States, specifically Arizona, New Mexico and Nevada.
Figure 6.5: Annual precipitation changes over North America from the A1B simulations.
Source: IPCC, Fourth Assessment, 2007. pg. 890
In southern Canada, precipitation is likely to increase in winter and spring, but decrease in
summer.
Although there will be greater volume of winter precipitation, much of this will fall as rain, which
naturally degrades ski conditions. Snow season length and snowpack depth are “very likely”
expected to decrease in most of North America, with the exception of northern Canada, an area
expected to realize both average temperature increases and an escalation in snow depths. This
bodes well for future prospects of ski resorts in these northern mountainous regions.
The primary factor leading to North America’s increasing temperatures and increasing
precipitation is the influence of mid-latitude cyclones. These are large traveling atmospheric
cyclonic storms up to 2000 kilometers in diameter with centers of low atmospheric pressure.51 As
42
the storm tracks shift poleward, the atmospheric moisture transport and convergence is projected
to increase, resulting in a widespread increase in annual precipitation over most of the continent
except the south and south-western part of the USA and Mexico.52
6.2.3.
Snowfall, Snowpack
Snow accumulations are projected to decrease overall due to delayed autumn snowfall and earlier
spring snowmelt. However in northern regions where winter precipitation is projected to increase,
the additional snowfall could more than make up for the shorter snow season and yield increased
snow accumulation in the next 20 – 30 years.
A similar scenario could unfold in the Rocky Mountains, although most models project a
widespread decrease of snow depth in this region.53
The graphic on the following page was adapted from the IPCC report and provides a snapshot of
long run trends affecting the globe during winter months. The blue shading in the background
signifies the expected increase in precipitation over much of North America, with the exception
being the southern latitudes regions of the Southwest and Mexico. The icons over North America
denote less snow and warmer temperatures in the Midwest and Rock Mountains, while increases
in precipitation in Canada.
43
Figure 6.6: Winter Trends Resulting from Warming
Source: IPCC, Fourth Assessment, 2007
44
7. Future Change In Regional Snowfall
While the efficiency of climate models continues to evolve, yielding ever more detailed
predictions, the GCM’s remain limited in their ability to forecast seasonal changes in specific
locations. It’s under this pretense that the paper will consider potential changes in snowfall and
the ensuing impact on the five (5) primary US ski regions. For these forecast the study relied on a
2000 report released by US Global Change Research Program (USGCRP), which bases
conclusions on the projections from the Hadley Centre in the United Kingdom and the Canadian
Centre for Climate Modeling and Analysis. This USGCRP study focuses on North America and
serves as a comprehensive resource for localized climate change forecasts.
Inputting these localized snowfall forecasts into the models elucidated in Chapter 5.0, the study
will interpolate future impacts to each region’s ski industry.
7.1.
Northeast
For the region as a whole, the period between the first and last dates with snow on the ground has
decreased by 7 days over the last 50 years, resulting in a shorter snow season.54 This observable
fact was clearly on display during the 2006/2007 season which did not realize appreciable
snowfall in the Northeast until mid-January.
Over the next 30+ years, USGCRP predicts increases in winter precipitation of upwards of 10%,
which will lead to increased snowfall during that timeframe. However as temperatures continue to
rise more of this precipitation will occur in the form of rain hampering ski conditions.
Using the Northeast model (Section 5.1.1) developed for this study, an increase in snowfall of
10% would result in approximately 170,000 additional annual skier visits. While statistically
speaking this figure is immaterial, the fact that there is a predicted increase is noteworthy for the
Northeast region. The formula follows below:
Formula 7.1:
SVNE = 10.68 + 0.0152 SFNE
The Northeast also features numerous microclimates which experience different changes. For
instance, the Great Lakes are very likely to experience decreased ice cover as warming
45
progresses. This reduction in ice cover will add significant moisture to southbound winter cold
fronts coming from Canada thereby fueling the “lake effect” snow storms that dump significant
amounts of snow on the Buffalo, NY area. Eventually, it’s expected that warming will turn this
precipitation into rain, but over the next 30+ years snowfall records are set to fall.55
7.2.
Southeast:
The Southeast will likely experience a high degree of warming. Here there is also an expectation
for increased precipitation. However this precipitation is expected to manifest itself as rain since
the average mean temperature is the highest of the five regions.
The USGCRP report predicts an increase in annual precipitation of 10 – 15%; however the
concurrent rise in temperatures will dramatically impact snowfall accumulation, resulting in a
loss of approximately 40%. Although the model (Formula 7.2) only projects an approximately
280,000 reduction in visits when this figure is input, there’s little doubt that severe reduction will
bring with it serious implication for all but the largest operators. We anticipate many closures
over the next three to four decades.
Formula 7.2: SVSE = 4.22 + 0.0107 SFSE
7.3.
Midwest
Throughout the 20th century, the northern portion of the Midwest, where the majority of resorts
are located, has warmed by almost 2.3oC (4.1°F). Annual precipitation has increased, up some
20% in areas, with much of this coming from singular heavy precipitation events.56
The length of the snow season over the last 50 years has increased by about 6 days per year in the
northern Great Lakes area. This trend is expected to continue over the next 30 years as the “lake
effect” on snowfall becomes more pronounced in this region, with an estimated 20% increase in
precipitation. Although counter intuitive, plugging this estimate into Midwest model (Formula
7.3) results in a negative impact on skier visits.
Formula 7.3: SVMW = 7.41 - 0.00132 SFMW
46
While statistically this result is irrelevant, it does serve to reinforce the argument posed in Section
5.1.3 that skier visits are negatively impacted by increases in snowfall due to skiers’ proclivity
towards more manageable conditions.
7.4.
Rocky Mountains
When considering the complex mountainous regions defining the landscape of the Rocky
Mountain region, studies point to a decline in winter snowpack and a hastening of snowmelt due
to regional warming57. This region has generally become wetter over the last century with
observed increases in precipitation in some areas greater than 50%.
Looking to the future, the temperature in the Rocky Mountain region is predicted to increase,
with a forecast decrease in precipitation. This recipe of warming combined with decreased
precipitation will result in shorter ski seasons. Resorts at lower elevations will experience the
most severe impact to their business.
The two models employed by USGCRP project a 3.8°F (2.1°C) winter warming and 4.8°F
(2.7°C) warming, respectively by the year 2030. While is there is generally dissention as to the
magnitude of change in snowfall, for the purposes of this study, the thesis will assume a 10%
decrease (Formula 7.4). This amount of decrease in snowfall would results in only a roughly 3%
impact to skier visits.
Formula 7.4: SVRM = 17.94 - 0.0048 SFRM
It is the author’s contention however; that there will be an observed increase in skier visits in 30+
years, as a high percentage of skiers from the enfeebled Southeast region will elect to travel west
to find superior conditions. The Rocky Mountain region stands to gain from this displaced
segment of the market.
7.5.
Pacific West
The Pacific West region has experienced warming of approximately 3°F (1.7°C) over much of the
region, with nearly equal warming in summer as has occurred in winter. The length of the snow
season in California and Nevada has decreased some 16 days from 1961 – 1996.58
47
Annual temperatures are projected to increase nearly 4°F by the year 2030, which will be
accompanied by considerable increases in winter precipitation. The greatest increase is expected
over California, where USGCRP reports as much as a 40% boost. Per the model (Formula 7.5),
this only nets a 6% increase in skier visits however, as much of this gain will come in the form of
rain, degrading skiing conditions.
Formula 7.5: SVPW = 8.97 + 0.0081 SFPW
Figure 7.1 illustrates the impact warming will have on the snow line, which will shift vertically
over 1,000 s.f. This will not have an immediate effect on resorts in the region, but serves as a
harbinger of things to come.
Figure 7.1: Estimated snowline shift by 2050, assuming about 4ºF warming.
Source: R. Leung, Pacific Northwest National Laboratory.
48
8. Adaptation and Risk Mitigations
Global warming will have an increasingly severe affect on the ski industry in the coming decades.
Although accurate weather forecasts are not available more than a week or so in advance, the fact
that there will be greater variability from year to year is indisputable. Recognizing this fact will
enable operators to plan accordingly and adopt strategies designed to minimize the negative
corollaries that follow. This section will examine the various tools available to stakeholders in the
winter recreation business and discuss the merits of each.
8.1.
Artificial Snowmaking
The most ubiquitous strategy to mitigate climate change risk is the installation of snowmaking
equipment. First implemented in 1953 at Grossinger's Resort in New York,59 snowmaking has
become a principle fixture in the industry, with an estimated 95% of resorts worldwide engaged
in snowmaking to some degree.60
While snowmaking offers an invaluable – some would argue superior – substitute to natural snow
during extended dry periods, the application of this technology is governed temperatures. Even
after advances that permit artificial snow creation at ever higher temperatures, Mother Nature
must still cooperate with both temperature and low humidity.61
Technological advances in snowmaking are reducing labor costs by enabling resorts to automate
the process. Keystone Resort recently installed snow guns operated by computers which adjust
air and water flows and automatically engages the system when weather conditions warrant. This
automation is increasingly valuable as warmer temperatures may only dip below freezing for
short spells and every moment available to make snow should be put to use.62
In a 2006 study, snowmaking was found to extend the average ski season in the Northeast by
between 55 – 120 days.63
There are concerns, in that the practice requires a considerable amount of water. Blanketing a
large resort can use millions of gallons of water each year.64 Therefore resorts must acquire legal
rights to water sources and/or install retention basins to collect and store runoff. As the industry’s
largest consumer of water, Vail Resorts has rights to more than 1 billion gallons of water held in
49
four reservoirs, as well as rights to water from creeks and streams near each of its four Colorado
ski areas65. This strategy has paid dividends for Vail, as they have been able to sustain their
snowmaking program in the driest of years.
8.2.
Weather Derivatives
Weather derivatives are a relatively new class of weather risk management tool that are structured
like classic put options, call options, and swaps in the capital markets. Today the capital markets
have an appetite for weather-related risk because it is, in principle, completely uncorrelated with
other market sectors.66
Reportedly the over-the-counter market began in 1996 when Koch Energy (now Entergy-Koch)
and Enron completed a swap for the winter of 1997 in Milwaukee, WI based on heating degree
days (HDD). Since this contract the industry has expanded rapidly, with an estimated $19.2
billion of contracts traded on the Chicago Mercantile Exchange during 2007, as reported buy the
Weather Risk Management Association (WRMA).67
The application of such derivatives is straightforward. In a typical temperature transaction if the
average temperature over a predefined time period exceeds a certain threshold, the buyer of the
contract is entitled to receive a payment from the seller based on the extent to which the average
temperature exceeds the aforementioned threshold. The amount of payment is determined at the
time the contract is executed and is predicated on the buyer’s sensitivity to adverse changes in
temperature – for example increased costs of artificial snow making.
In the context of a ski area operator, derivative agreements can be structured based on snowfall
and/or temperature. For instance, to protect against a dry snow season, a ski area might buy a
snowfall put option, which is structurally equivalent to snowfall insurance. Additionally the resort
operator might sell a snowfall call option or buy a swap, which would effectively provide a
“revenue backstop” in the event of low snowfall.
Another application would be to use weather derivatives to finance marketing promotions
intended to increase patronage (see 8.5 below). For instance a ski area could structure an
advertising campaign in which a refund would be paid if snowfall over a 5-7 day period is below
50
a predefined minimum. For a fixed price, the resort could completely hedge this exposure using
weather derivatives.
Weather derivatives serve as a more cost effective hedge against weather risk than insurance
policies, which have become increasingly expensive in light of recent poor snowfall seasons. In
1999-2000, Vail Resorts bought "reduced skier-day" insurance that paid $13.9 million when the
resort didn't get much snow and lift ticket sales were down substantially. After that, insurance
prices rose and Vail no longer carries such insurance.68
8.3.
Revenue Diversification
As the skiing industry continues to grow and broaden its customer base, one of the key strategies
is to develop new compelling entertainment offerings which cater to the non-skiing consumer.
There are wide varieties of offerings available to engage and delight customers with all
preferences. For examples, many resorts offer snowmobiling or cross-country skiing to the active
non-downhill skier. While more passive activities involve high-end day spas, indoor pools, retail
shopping alternatives, and fine dining establishments.
Another method of diversification available to large scale operators is the
acquisition/development of resorts in dissimilar geographic locations. While in any given year
snow conditions could be poor in specific regions, the risk to operators is greatly assuaged by
owning operations in disparate areas that are exposed to completely different weather patterns.
For example, during the 2004/2005 season Booth Creek, the fourth largest ski resort owner in
North America, was able to relieve some of the financial stress felt at Summit at Snoqualmie, due
to exceptionally poor conditions in the Pacific Northwest. The company relocated employees to
their two California resorts and honored Summit at Snoqualmie season passes at other resorts in
their portfolio. In another goodwill gesture, Booth Creek allowed season pass holders, who
account for approximately half of skier visits, to extend their passes through the next season at no
cost.69
8.4.
Cloud Seeding
Employed by a handful of resorts in a bid to cause bountiful snowfall, cloud seeding is a process
by which either dry ice or, more commonly, silver iodide aerosols are released into the upper part
51
of clouds in order to fuel the precipitation process. Since most rainfall starts through the growth
of ice crystals from super-cooled cloud droplets (droplets colder than the freezing point, 32 deg.
F) in the upper parts of clouds, the silver iodide particles are meant to encourage the growth of
new ice particles.70
A recent study from the Bureau of Reclamation estimates that in an average precipitation year,
about one million acre-feet of additional snowpack water could be produced by seeding.71
However the practice is expensive and a large majority of resorts remain skeptical as to its merits.
8.5.
Marketing
There are a wide variety of marketing initiatives available to assuage growing concerns over
conditions, specifically during the early and late stages of each season. Resorts often cater to a
stratified audience, namely local day visitors as well as destination travelers, therefore it’s
imperative for resorts to tailor marketing efforts to both groups.
Marketing season passes to locals is a basic means to insulate against losses resulting from shortterm fluctuations in weather, as locals are the most likely to cancel plans in response to marginal
conditions. Vail, for instance, realized a quarter of their FY06 lift ticket revenue from season pass
sales.
There are also a variety of marketing incentives intended to give customers comfort around
booking early. For instance, during the 1999/2000 season, the American Ski Company guaranteed
visitors to several of their New England resorts a 25% reduction on their next vacation in the
event less than 70% of the skiable terrain was open during the Christmas/New Year holiday.
Three of the resorts ended up having to provide these rebates due to warm temperatures.72
While these rebates can be costly, there are strategies to hedge this exposure, such as using
weather derivatives as discussed in Section 8.2.
Finally, good old fashion luck can often serve as effective marketing. It’s been reported than
when Denver hosts Monday Night Football and snow is falling, Colorado resorts receive a surge
in advance reservations. This is not backed up by hard statistics; but empirics strongly suggest it
is true.73
52
9. Conclusion
Although the study confirms that claims of the imminent demise of the United States’ ski
industry at the hands of climate change are overstated, it is evident that this phenomenon
poses a continuing long term threat the business.
The simple model employed for this paper demonstrates that the level of snowfall is only
one of many variables that drive skiers’ decisions whether to visit a particular resort.
Savvy operators should be able to withstand poor snow seasons through a calculation
application of any one or more of the techniques chronicled in this study.
While those resorts that rely on weekend skier visits, namely the Northeast, Southeast,
and Pacific West, are most susceptible to the vicissitudes of snowfall, these resorts can
counteract this risk through snowmaking, weather derivatives, or by diversifying their
entertainment offerings.
Even with these new innovations however, there will come a time when daily temperatures
simply will not support the creation of artificial snow and the preference of customer base will
permanently adjust. Therefore it is imperative for today’s resort developers to look beyond the
classic short term business planning and investment time horizons and commit resources to
address these long run concerns.
A well founded investment in regions that today perhaps are considered too frigid and uninviting
might well hold the promise of considerable returns should conditions shift as forecast. This
presents the ideal scenario to attract skiing enthusiasts, an audience that is not deterred by travel.
This is supported by a survey of skiers which shows that this group will respond flexibly to
changing snow conditions. During a period of snow-poor seasons, a 2003 study found that 49%
of skiers would change to a ski resort that is more snow-reliable. 32% of skiers would ski less
often and only 4% of respondents would chose not to ski.74 This represents a paradigm shift in
the industry and an opportunity for savvy resort developers to capture this displaced market.
53
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58